8. Experimental animals Provide species-appropriate details of the animals used, including species, strain and substrain, sex, age or developmental stage, and, if relevant, weight. explanation

The species, strain, substrain, sex, weight, and age of animals are critical factors that can influence most experimental results [1-5]. Reporting the characteristics of all animals used is equivalent to standardised human patient demographic data; these data support both the internal and external validity of the study results. It enables other researchers to repeat the experiment and generalise the findings. It also enables readers to assess whether the animal characteristics chosen for the experiment are relevant to the research objectives.

When reporting age and weight, include summary statistics for each experimental group (e.g. mean and standard deviation) and, if possible, baseline values for individual animals (e.g. as supplementary information or a link to a publicly accessible data repository). As body weight might vary during the course of the study, indicate when the measurements were taken. For most species, precise reporting of age is more informative than a description of the developmental status (e.g. a mouse referred to as an adult can vary in age from six to twenty weeks [6]). In some cases, however, reporting the developmental stage is more informative than chronological age, for example in juvenile Xenopus, where rate of development can be manipulated by incubation temperature [7].

Reporting the weight or the sex of the animals used may not be feasible for all studies. For example, sex may be unknown for embryos or juveniles, or weight measurement may be particularly stressful for some aquatic species. If reporting these characteristics can be reasonably expected for the species used and the experimental setting but are not reported, provide a justification. 

References

1. Clayton JA and Collins FS (2014). Policy: NIH to balance sex in cell and animal studies. Nature News. doi: 10.1038/509282a
2. Shapira S, Sapir M, Wengier A, Grauer E and Kadar T (2002). Aging has a complex effect on a rat model of ischemic stroke. Brain Res. doi: 10.1016/s0006-8993(01)03270-x
3. Vital M, Harkema JR, Rizzo M, Tiedje J and Brandenberger C (2015). Alterations of the murine gut microbiome with age and allergic airway disease. J Immunol Res. doi: 10.1155/2015/892568
4. Bouwknecht JA and Paylor R (2002). Behavioral and physiological mouse assays for anxiety: a survey in nine mouse strains. Behavioural brain research. doi: 10.1016/s0166-4328(02)00200-0
5. Simon MM, Greenaway S, White JK, Fuchs H, Gailus-Durner V, Wells S, Sorg T, Wong K, Bedu E, Cartwright EJ, Dacquin R, Djebali S, Estabel J, Graw J, Ingham NJ, Jackson IJ, Lengeling A, Mandillo S, Marvel J, Meziane H, Preitner F, Puk O, Roux M, Adams DJ, Atkins S, Ayadi A, Becker L, Blake A, Brooker D, Cater H, et al. (2013). A comparative phenotypic and genomic analysis of C57BL/6J and C57BL/6N mouse strains. Genome Biol. doi: 10.1186/gb-2013-14-7-r82
6. Jackson SJ, Andrews N, Ball D, Bellantuono I, Gray J, Hachoumi L, Holmes A, Latcham J, Petrie A, Potter P, Rice A, Ritchie A, Stewart M, Strepka C, Yeoman M and Chapman K (2017). Does age matter? The impact of rodent age on study outcomes. Laboratory Animals. doi: 10.1177/0023677216653984
7. Khokha MK, Chung C, Bustamante EL, Gaw LW, Trott KA, Yeh J, Lim N, Lin JC, Taverner N, Amaya E, Papalopulu N, Smith JC, Zorn AM, Harland RM and Grammer TC (2002). Techniques and probes for the study of Xenopus tropicalis development. Dev Dyn. doi: 10.1002/dvdy.1018